Implement CQRS Architecture
CQRS implementation: command and query buses, FastAPI endpoints, read model sync, and eventual consistency.
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Why it matters
Implement Command Query Responsibility Segregation (CQRS) patterns to decouple read and write operations, enabling independent scaling and optimized data modeling for complex systems.
Outcomes
What it gets done
Define command and query models with clear boundaries.
Implement read model projections and synchronization strategies.
Validate performance, recovery, and failure modes of the CQRS implementation.
Guide separation of read/write concerns for scalable applications.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-cqrs-implementation | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
CQRS implementation with command and query bus infrastructure, a FastAPI CQRS application template, read-model synchronization, and eventual-consistency handling. Use when separating command and query paths, building a command or query bus, or synchronizing a read model from events.
What it does
Diagrams the CQRS architecture splitting a client's writes and reads into separate Commands and Queries APIs, each with its own handlers, where command handlers write to a write model that emits events to update a separate read model, and defines six components: Command as the intent to change state, Command Handler validating and executing it, Event as the record of the change, Query as a data request, Query Handler retrieving from the read model, and Projector updating the read model from events. Ships five templates: command infrastructure (a Command dataclass base auto-generating a command_id and timestamp, concrete commands like CreateOrder, AddOrderItem, and CancelOrder, a generic CommandHandler abstract base, a CommandBus that registers handlers by command type and dispatches to them, and a CreateOrderHandler implementation that validates the command, creates an Order aggregate, and persists its uncommitted events to an event store under a stream ID), query infrastructure (a parallel Query base, concrete queries, typed query results, a QueryHandler base, and a QueryBus), a FastAPI CQRS application (request and response models, dependency injection, POST, PUT, and DELETE command endpoints, and GET query endpoints), read model synchronization, and eventual consistency handling (a ConsistentQueryHandler implementing read-your-writes consistency by polling a projection_state table for the last-processed event version against an expected_version, retrying every 100ms until it catches up or a timeout elapses, at which point it returns the possibly-stale data with an explicit _warning field reading 'Data may be stale' rather than silently returning it as fresh).
When to use - and when NOT to
Use it when separating command and query paths in an application, building a command or query bus, wiring a FastAPI CQRS API, synchronizing a read model from events, or handling eventual consistency between write and read models. Skip it for anything unrelated to CQRS implementation or outside this scope.
Inputs and outputs
Input is a use case requiring separated write and read paths - an order-processing system, an event-sourced aggregate, or an API needing independently-scaled reads and writes; output is the matching command or query class, handler, bus registration, or FastAPI endpoint, following the documented CQRS component responsibilities.
Integrations
Framework-agnostic command and query bus infrastructure in plain Python (dataclasses, ABCs, generics) with a FastAPI-specific template for exposing commands and queries as REST endpoints. Assumes an event store as a pluggable dependency for persisting command-generated events.
Who it's for
Backend engineers implementing CQRS who need concrete command bus, query bus, and read-model synchronization code rather than an abstract explanation of separating reads from writes.
FAQ
Common questions
Discussion
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